Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks

D. Aleksendrić, I. Balać, Chak Yin Tang, Chi Pong Tsui, P. S. Uskoković, D. P. Uskoković

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


In this paper, the mechanical properties of polymer matrix phase (modulus of elasticity, yield stress and work hardening rate) have been determined using combined methods such as nanoindentation, finite element modelling and artificial neural networks. The approach of neural modelling has been employed for the functional approximation of the nanoindentation load-displacement curves. The data obtained from finite element analyses have been used for the artificial neural networks training and validating. The neural model of polymer matrix phase of poly-l-lactide (PLLA) polymer in hydroxyapatite (HAp)/PLLA mechanical behaviour has been developed and tested versus unknown data related to the load-displacement curves that were not used during the neural network training. Based on this neural model, the nanoindentation matrix phase properties of PLLA polymer in HAp/PLLA composite have been predicted.
Original languageEnglish
Pages (from-to)65-70
Number of pages6
JournalAdvances in Applied Ceramics
Issue number2
Publication statusPublished - 1 Feb 2010


  • Artificial neural networks
  • Biocomposites
  • Finite element model
  • Nanoindentation

ASJC Scopus subject areas

  • Ceramics and Composites
  • Industrial and Manufacturing Engineering

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